The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
It is known to correct colors in pictures or in some parts of the pictures to improve the perceptual experience. As an example, pictures with saturated colors are advantageously processed to remove these saturated colors and thus improve the perceptual experience.
Document entitled “Color Harmonization” from Cohen-Or teaches a method for harmonizing pictures based on harmonious color templates. An harmonious color template Tm,α is defined by a template type m and an angle α. These harmonious color templates are depicted on FIG. 1. This method has the several drawbacks. First, it is not fully automatic and requires manual annotation for “sensitive” areas (typically skin or sky that look unnatural if they lose their original color). Second, color mapping is very basic. It maps color palette of the original picture by applying a Gaussian filter constraint in a template.
In order to harmonize the colors of a video, each individual picture of the video can be processed independently for example by applying the method of Cohen-Or. However, processing each picture independently results in artifacts such as flickering. In order to overcome this drawback, Sawant et al in “Color harmonization for Videos” published in Indian Conference on Computer Vision, Graphics and Image processing in 2008 teaches to compute a hue histogram for a current picture taking into account the pixels values of a N subsequent pictures. The hue histogram for the group of pictures that comprises the current picture and the N subsequent pictures is the mean of the hue histograms computed for each individual picture. The template type m is set to “X” and the template orientation a is computed from the group's histogram. All the pictures belonging to that particular group are harmonized with this calculated a. Finally, to avoid changes at group boundaries, some overlapping between groups is considered to compute the hue histogram. When computing the template from several pictures according to this method, the content of a single image can greatly impact the result, such as in the case of a flash, or of a scene change. When the type of the template or when the value of a abruptly changes, a visible temporal change can appear in the resulting video.